Create app.py

app.py

@@ -0,0 +1,77 @@
+import torch
+import gradio as gr
+from diffusers import FluxPipeline
+from huggingface_hub import hf_hub_download
+import os
+import random
+
+# Chargement du modèle Flux.1-schnell (Apache 2.0, NSFW-friendly)
+model_id = "black-forest-labs/FLUX.1-schnell"
+pipe = FluxPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16)
+pipe.enable_model_cpu_offload()
+pipe.enable_sequential_cpu_offload()  # Optimise VRAM pour Space gratuit
+
+# Variables globales pour LoRA
+lora_repo = None
+lora_strength = 0.8
+
+def load_lora(repo_id):
+    global pipe, lora_repo
+    try:
+        lora_path = hf_hub_download(repo_id=repo_id, filename="flux-lora.safetensors")
+        pipe.load_lora_weights(lora_path)
+        pipe.fuse_lora()
+        lora_repo = repo_id
+        return f"LoRA chargé : {repo_id}"
+    except Exception as e:
+        return f"Erreur LoRA : {str(e)}"
+
+def generate(prompt, negative_prompt, width=1024, height=1024, steps=4, seed=-1, lora_scale=0.8):
+    global pipe, lora_repo, lora_strength
+    pipe.set_lora_scale(0.0)  # Reset LoRA
+    if lora_repo:
+        pipe.set_lora_scale(lora_scale)
+    
+    generator = torch.Generator(device="cuda" if torch.cuda.is_available() else "cpu").manual_seed(seed if seed != -1 else random.randint(0, 2**32))
+    
+    # Params optimisés pour NSFW : faible guidance (Flux flow-based), steps rapides
+    image = pipe(
+        prompt,
+        height=height, width=width,
+        num_inference_steps=steps,
+        guidance_scale=0.0,  # Pas de CFG pour Flux naturel
+        max_sequence_length=512,
+        generator=generator,
+        negative_prompt=negative_prompt
+    ).images[0]
+    return image
+
+# Interface Gradio favorisant NSFW
+with gr.Blocks(title="Flux Schnell NSFW LoRA Space", theme=gr.themes.Dark()) as demo:
+    gr.Markdown("# Flux.1 Schnell + LoRA NSFW\nGénérateur rapide (4 steps) pour images explicites. Ajoutez LoRA NSFW de HF/Civitai.")
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            lora_input = gr.Textbox(label="Repo HF LoRA (ex: XLabs-AI/flux-lora-collection ou NSFW)", value="")
+            load_btn = gr.Button("Charger LoRA")
+            status = gr.Textbox(label="Status LoRA")
+        
+        with gr.Column(scale=4):
+            prompt = gr.Textbox(label="Prompt NSFW", placeholder="Fille nue réaliste, pose sexy, éclairage studio, haut détail, 8k", lines=3, value="beautiful naked woman, detailed anatomy, erotic pose, realistic skin, soft lighting")
+            neg_prompt = gr.Textbox(label="Negative", value="blurry, deformed, ugly, lowres, text, watermark")
+    
+    with gr.Row():
+        steps = gr.Slider(1, 20, value=4, label="Steps (4=rapide)")
+        width = gr.Slider(512, 2048, value=1024, step=128, label="Largeur")
+        height = gr.Slider(512, 2048, value=1024, step=128, label="Hauteur")
+        lora_scale_slider = gr.Slider(0, 2, value=0.8, label="Force LoRA")
+        seed = gr.Number(value=-1, label="Seed (-1=random)")
+    
+    generate_btn = gr.Button("Générer Image NSFW", variant="primary")
+    output = gr.Image(label="Résultat")
+    
+    load_btn.click(load_lora, inputs=lora_input, outputs=status)
+    generate_btn.click(generate, inputs=[prompt, neg_prompt, width, height, steps, seed, lora_scale_slider], outputs=output)
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=7860)